Entries

22 Sep 2008

This paper, presented at ICFP'08, describes ML
type inference in an entirely graphical setting, and shows that
MLF type inference is only a very simple generalization of
the ML case. Our approach is constraints-based; we give some
equivalence rules on constraints, as well as an algorithm
to solve them.
We also show that type inference for MLF
has linear complexity in practice, as in ML.

The full abstract for the paper can be found
in my publications page.
Compared to the published version,
this version corrects
some small mistakes in Definitions 9 and 11, and in Figure 17.
The long version is available as Part 2 of my
PhD dissertation.